WeSearch
Hub / Tags / Machinelearning
TAG · #MACHINELEARNING

Machinelearning coverage.

Every story in the WeSearch catalog tagged with #machinelearning, chronological, with view counts. Subscribe to the per-tag RSS feed to follow this topic in your reader of choice.

60 stories tagged with #machinelearning, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.

⌘ RSS feed for this tag →   or   search "Machinelearning"

RELATED TAGS
#ai119#programming22#technology17#python15#opensource9#llm9#security9#datascience8#webdev7#infrastructure6#computervision5#rag5
DEVARSH RANPARA

The Smallest Brain You Can Build: A Perceptron in Python

A perceptron explained from scratch in Python, with interactive demos. Learn weights, bias, the decision boundary, epochs, learning rate, and why we normalize data.…

47 views ·
#neuralnetworks#python
DEV.TO (TOP)

Agentes de IA: cómo un LLM razona, usa herramientas y actúa solo

Un agente de IA es un LLM metido en un bucle que razona, elige herramientas y ejecuta acciones hasta cumplir una meta. Te explicamos cada pieza con có…

18 views ·
#ai#technology
DEV.TO (TOP)

GitHub Copilot's New Desktop App Isn't About Chat. It's About Agents.

Microsoft's latest announcements from Build 2026 signal a fundamental shift. The new GitHub Copilot desktop app is a move from inline code completion to a native environment for ag…

17 views ·
#ai#devtools
DEV.TO (TOP)

How to make your first Machine Learning project (as an absolute beginner)

Making your first Machine Learning project as beginner can be daunting. To be honest, I was daunted....…

15 views ·
#tutorial#beginners
DEV.TO (TOP)

I Built a Vector Search Engine from Scratch — Here's What I Learned

I Built a Vector Search Engine from Scratch — Here's What I Learned Implementing HNSW...…

13 views ·
#programming#algorithms
DEV.TO (TOP)

Understanding Linear Regression: A Foundation of Machine Learning

Linear Regression is one of the most fundamental and widely used algorithms in Machine Learning and...…

12 views ·
#statistics#programming
DEV.TO (TOP)

NVIDIA Put Petaflop Compute on Your Desk — And It Changes the AI Cost Equation

NVIDIA Put Petaflop Compute on Your Desk — And It Changes the AI Cost Equation At GTC...…

20 views ·
#ai#nvidia#technology
DEV.TO (TOP)

Day 5 — Entering the World of Classification

Today I started Week 3 of the Machine Learning Specialization and learned about...…

13 views ·
#ai#datascience
DEV.TO (TOP)

AI.Insaf (@ai_tablet) — Полный архив постов канала

## Ранние посты (#1-~49)…

10 views ·
#ai#data
DEV.TO (TOP)

AI.Insaf — Архив постов канала (реальные посты из web_fetch)

**Канал:** https://t.me/ai_tablet…

17 views ·
#ai#data
DEV.TO (TOP)

Running 35B–400B LLMs on a GPU-less Cluster to Mine 10,000 Papers — and the 4 Bugs That Almost Ruined the Data

A field report: a CPU-only, GPU-less distributed LLM pipeline (llama.cpp + quantized MoE) mining 10,000 papers — and the 4 silent data-quality bugs that nearly ruined the results.…

15 views ·
#dataextraction#infrastructure
DEV.TO (TOP)

Retrieval Found the Sensitive Memory. That Made It More Dangerous.

This continues the research on why relevance alone is insufficient for agent memory safety. Article...…

15 views ·
#ai#security
DEV.TO (TOP)

I Tried to Turn Agent Memory Authority Into a Scoring Formula. The Held-Out Test Changed the Claim.

A few articles back, a good friend asked a question I could not deflect. He had read the earlier...…

12 views ·
#ai#agentmemory
DEV.TO (TOP)

How I Built a Real-Time Fraud Detection System That Handles 71,000 RPS at p95 <6ms

How I Built a Real-Time Fraud Detection System That Handles 71,000 RPS at p95 &lt;6ms A...…

16 views ·
#frauddetection#programming
DEV.TO (TOP)

Notes from the Mistral AI Now Summit

It’s hard to believe how quickly the tech landscape is evolving, especially with AI/ML at the...…

21 views ·
#ai#ethics
DEV.TO (TOP)

Power Management Strategies for Battery-Powered Edge AI Devices

Design patterns and firmware techniques to extend battery life for edge AI devices: DVFS, PMIC control, duty-cycling, sensor scheduling, and measureme…

18 views ·
#embedded#powermanagement
DEV.TO (TOP)

AI Placement Decisions Are Architecture, Not Optimization

AI placement latency is not the problem most teams think they are managing. The default framing...…

11 views ·
#ai#infrastructure
DEV.TO (TOP)

Why the Treasure Hunt Demo Broke Every Query Tool We Fed It

The Problem We Were Actually Solving We were not building a demo. We needed to let Veltrix...…

14 views ·
#webdev#programming#ai
DEV.TO (TOP)

From NumPy to JAX: My First "Aha!" Moments with Accelerated AI

Building open-source solutions for my 100 Days of AI Agents challenge meant I needed to start looking...…

22 views ·
#python#jax
DEV.TO (TOP)

The Open Source Illusion: Why "Free" AI Models Are Getting Expensive

The Open Source Illusion: Why "Free" AI Models Are Getting Expensive Everyone's watching...…

15 views ·
#ai#open-source
DEV.TO (TOP)

I tracked Claude Code and Codex pass-rates for 95 days — what "getting dumber" actually looks like

Every few weeks a thread blows up: "Is Claude Code getting worse?" Someone swears Opus got lazy after...…

11 views ·
#ai#programming
DEV.TO (TOP)

Fine-Tuning Qwen2.5-0.5B to Write SRE Post-Mortem Summaries

Writing post-mortem root-cause summaries is time-consuming and inconsistent. Junior SREs miss...…

11 views ·
#ai#sre
ROUNDTABLE RESEARCH

CAPTCHAs can still detect AI agents

AI systems now match human solutions on many tasks, but reach those solutions via measurably different processes. This gap can be exploited to detect AI agents and online bots.…

16 views ·
#ai#captcha
DEV.TO (TOP)

El consumo eléctrico de la IA varía hasta 300x entre tareas

Un benchmark de la Universidad de Michigan mide el consumo eléctrico real de los modelos de IA y revela diferencias de hasta 300x según la tarea.…

11 views ·
#ai#energy
DEV.TO (TOP)

Handling Failure: The Most Important Part of AI Systems

Every AI system will fail. The question isn't whether it will happen. The question is: What...…

11 views ·
#ai#mlops
DEV.TO (TOP)

How Model Distillation Actually Works (and What the 'China Distilled Our Model' Headlines Really Mean)

A practical, no-hype explainer of knowledge distillation in LLMs — the actual mechanics, why distilling from a closed API is different, and what the OpenAI/Anthropic vs DeepSeek al…

18 views ·
#ai#deeplearning
DEV.TO (TOP)

I Blamed the Model for Months. The Bug Was My Sampler.

I Blamed the Model for Months. The Bug Was My Sampler. 40GB In, Word Salad...…

10 views ·
#apple#programming
DEV.TO (TOP)

MaaS 2026: Beyond the 'Model Supermarket' — The Infrastructure Battle

title: "MaaS 2026: Beyond the 'Model Supermarket' — The Infrastructure Battle" published:...…

16 views ·
#ai#infrastructure
DEV.TO (TOP)

Rudi AI Is a Character Wrapper Over Grok 4. Here Is What That Architecture Teaches Us About Building Persona-Driven AI Products.

Full product overview and parental controls guide: Aadhunik AI - Inside Rudi AI, Grok's Cute...…

14 views ·
#ai#productdesign
DEV.TO (TOP)

Tensors Explained Part 2: Why Tensors Are Useful

In the previous article, we started with a brief introduction to tensors. In this article, we will...…

11 views ·
#ai#tensors
DEV.TO (TOP)

Data Scientist & AI Engineer — Open to Full-Time Opportunities

Hey Dev.to the community, I'm Ashwin Gururaj — a Data Scientist &amp; AI Engineer based in...…

9 views ·
#career#hiring
DEV.TO (TOP)

I Built a Local AI Agent That Thinks Like a Brain, Not a Database

I Built a Local AI Agent That Thinks Like a Brain, Not a Database Most AI agents today are...…

18 views ·
#ai#privacy
WITHEMISSARY

Building Trustworthy LLM Judges

The LLM-as-Judge An LLM-as-Judge is a language model used to evaluate the output of an AI system against a rubric. The judge consumes some combination of……

10 views ·
#ai#llm
DEV.TO (TOP)

We Didn’t Just Train AI on the Internet. We Started Training It on Itself.

There’s a quiet assumption in almost every AI discussion right now: “If we scale compute and...…

13 views ·
#ai#datascience
DEV.TO (TOP)

Federico@Cursor,Dimma@Fireworks深入探讨Composer2技术

红杉资本邀请Federico-Cassano@Cursor、Dmytro-Dzhulgakov(Dimma)@Fireworks,深入探讨Composer2技术 这个视频是红杉资本(Sequoia...…

22 views ·
#ai#softwareengineering
DEV.TO (TOP)

Why your quantized LLM loses its MTP heads and how to keep them

Quantizing a model with multi-token prediction heads? Here's why standard conversion pipelines drop them silently, and how to preserve and calibrate them.…

10 views ·
#llm#quantization
DEV.TO (TOP)

Anthropic's New Security Tooling is a Wake-Up Call for Agent Builders

The new Claude security guidance plugin and self-hosted sandbox aren't just features. They represent a fundamental shift towards treating agent security as an infrastructure proble…

16 views ·
#ai#security
DEV.TO (TOP)

I Thought AI Was Slow Because It Wasn't Smart Enough. Turns Out It's Exhausted From Carrying Things.

I've been working on a question lately: can an AI run on a small local device without depending on...…

15 views ·
#ai#hardware
DEV.TO (TOP)

AllReduce Stalls Are Network Stalls. Most Tools See Neither.

A slow AllReduce on rank 5 lines up against TCP retransmits on rank 5’s NIC, four ms before the...…

12 views ·
#devops#performance
DEV.TO (TOP)

How DeepMind AlphaProof Nexus Cracks 56-Year-Old Math: Agentic LLM Loops and Lean Formal Verification

How Google DeepMind's AlphaProof Nexus Cracks 56-Year-Old Math Problems: A Deep Dive into...…

21 views ·
#ai#mathematics
DEV.TO (TOP)

Next.js 16 RAG Pipeline Optimization: Give Your AI a Perfect Memory

RAG (Retrieval-Augmented Generation) is the foundation of knowledge-grounded AI. But most RAG...…

14 views ·
#nextjs#ai
DEV.TO (TOP)

LLM-as-judge variance broke our DPO training signal for 3 weeks

TL;DR: Our DPO pipeline used a single LLM as the preference judge. Training reward climbed every run....…

16 views ·
#llm#mlops
DEV.TO (TOP)

Bayesian Knowledge Tracing in 37 lines of Python — how NumPath models what a student knows

What We Built NumPath maintains a KCState for every student × Knowledge Component pair....…

19 views ·
#education#bayesian
DEV.TO (TOP)

Built a Sentiment Analysis Web App – My First Full-Stack ML Project

Hey dev.to 👋 After spending a month learning Machine Learning through Andrew Ng’s specialization, I...…

19 views ·
#webdev#programming
DEV.TO (TOP)

How to Brier-grade your own ML option-pricing forecasts in 40 lines of Python

A walkthrough of one recipe from a new open-source cookbook for the Helium MCP REST surface. Log a model's prob_itm forecast today, append the realized outcome at expiration, compu…

19 views ·
#python#finance
DEV.TO (TOP)

Your Treasure Hunt Engine Was Probably a Latency Minefield (And Heres the Postmortem)

We had just finished the first major traffic spike. Our Veltrix-based treasure hunt game ran...…

18 views ·
#ai#webdev
DEV.TO (TOP)

I Let AI Replace Me for a Week as a (Kinda Junior) AI Engineer 😅

I recently tried using only ChatGPT + Claude for most of my day-to-day work as someone building...…

19 views ·
#ai#programming#productivity
DEV.TO (TOP)

I Built a Profiler to Audit My Own AI Tool Calls. Here's What I Learned About Observability

I built a profiler to audit my own tool calls. After loading 157 skills in 12 days, I realized I had...…

20 views ·
#ai#automation
DEV.TO (TOP)

Capping VLM spend per CV researcher: hierarchical budgets in practice

TL;DR: Our 11-person CV team at Prophesee was burning through €3-4k weeks of VLM spend on dataset...…

15 views ·
#computervision#mlops
DEV.TO (TOP)

Token-level eval harness for tool-calling agents: what we wired up

TL;DR: We replaced our "did the agent finish the task" pass/fail eval with a token-level harness that...…

20 views ·
#mlops#devops
DEV.TO (TOP)

RAG Is Not Always the Answer Anymore: How AI Agents Search Code in 2026

Why modern AI coding agents often use grep, file reads, symbols, and tests before reaching for vector RAG.…

16 views ·
#ai#programming
DEV.TO (TOP)

What I learned testing AI text detectors in 2026 (they still get it wrong)

If you build anything that touches user generated text, sooner or later someone asks: can we just...…

12 views ·
#ai#writing
DEV.TO (TOP)

Transformer as an Incomplete Cognitive Architecture: What It Captures Well and What It Misses (A11 Perspective)

Since its introduction, the transformer architecture has become the cornerstone of modern artificial...…

12 views ·
#ai#architecture
DEV.TO (TOP)

Apple Silicon's AI Ceiling Is Higher Than You Think

The consensus narrative around Apple Silicon and local AI inference goes something like this:...…

12 views ·
#ai#apple
DEV.TO (TOP)

GUI Agents vs RPA: Different Architectures for Different Problems

Desktop automation has reached an inflection point. For two decades, Robotic Process Automation (RPA)...…

12 views ·
#automation#ai
DEV.TO (TOP)

The Machine Learning Engineering Series

Part 1: From Scratch to Systems . This machine learning series will be a real ride. It’s...…

13 views ·
#ai#deeplearning
DEV.TO (TOP)

Master RAG Systems: Build an End-to-End LangChain Pipeline with Milvus, Reranking & Azure OpenAI 🚀

Beyond Basic RAG: Learn LangChain + RAG End-to-End 🚀 ...…

20 views ·
#ai#python
DEV.TO (TOP)

Beyond Autonomous AI: Understanding Self-Healing Agents in Enterprise AI Systems

Beyond Autonomous AI: Understanding Self-Healing Agents in Enterprise AI Systems 🧠🤖 As I...…

16 views ·
#ai#automation
DEV.TO (TOP)

Why Tesla Is Becoming the AI Enterprise Case Study Every Leader Should Understand

When executives talk about their "AI strategy" these days, they usually mean one of two things. They...…

16 views ·
#tesla#ai
DEV.TO (TOP)

Running ASR for smart homes in the NPU of Intel processors

I run my own smart home — Home Assistant, voice assistant pipeline, the whole self-hosted thing. The...…

17 views ·
#smarthome#intel